Research Engineer, Multimodal AI: Google DeepMind

Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.

About the Role:
As a Research Engineer on the REMY (Research & dEvelopment in Multimodal technologY) team, you will have the opportunity to push forward state-of-the-art research in multimodal AI representation models. You'll be at the forefront of developing models that power Google products used by billions of people worldwide, directly impacting how these products understand and interact with images, text, and video. Your work will include researching new modeling techniques, implementing research ideas, running experiments to evaluate improvements, and identifying new opportunities.

Key Responsibilities:

Conduct core research in the areas of computer vision, language understanding, multimodal models, and large-scale AI models.

Train and evaluate AI models for a variety of use cases.

Research, implement, and adapt state-of-the-art deep learning approaches for Google’s use cases.

Collaborate closely with other Google DeepMind and partner teams to make progress towards building the most advanced representation models.

Investigate and develop novel solutions by studying related work, conducting experiments, and constructing prototypes.

Transform successful prototypes into scalable solutions for wider integration within Google's products.

Requirements:

Ph.D. in Computer Science or a related quantitative field, OR

B.S./M.S. in Computer Science or a related quantitative field with 2+ years of relevant experience.

Ability to innovate and assess new machine learning models and techniques for pilot projects.

Experience collaborating with product teams to drive the implementation of research insights.

In addition, the following would be an advantage:

Strong research experience and a publication record in top-tier conferences.

Experience with core software engineering and applied implementations of AI.

A good team player who has demonstrated the ability to work across teams.